Tea Factory Research Articles

Assessment of the perceptions of tea farmers on the effect of temperature and rainfall variation on tea production in Kisii County

Kisii County’s agricultural systems largely depends on rain-fed conditions which are affected by the weather instabilities that cause climate variability. This has led to fluctuations in diverse crop production and in particular tea yields. The study aimed to assess the perceptions of tea farmers on the effect of temperature and rainfall variation on tea production in Kisii County. The study adopted a correlational research design. The sample size was 400 farmers but only 352 farmers returned duly signed questionnaires. The study targeted small scale tea farmers, Kisii Meteorological Department, and three Kenya Tea Development Agency factories of Kisii County. The study used questionnaires to collect primary data from small scale tea farmers and document analysis was used to collect secondary data. Interview schedules were used to collect data from the field service coordinators who were key informants. Primary data collected from small scale tea farmers included their perception on the effect of temperature and rainfall variability on tea production. Purposive and random sampling were used to choose tea factories and farmers respectively. The findings of the study reveals that the perception of the farmers concerning the effects of temperature is that scanty rainfall reduces tea yields, heavy rainfall causes erosion of top soil and washes away available fertilizer thus affecting tea production, and that frostbites reduce tea yields and production significantly since hailstones destroy the tea leaves and reduces tea yields drastically.

Research on Intelligent Blending Method of Matcha Based on Improved PID Control Algorithm

Most of the existing Matcha blending is done manually, which is inefficient and leads to uneven tea products. To solve this problem, this paper proposes an intelligent blending method based on improved PID control algorithm. In this paper, considering the various factors that affect the quality of tea, without affecting the quality of the product, taking the lowest cost of the enterprise as the constraint goal, the basic combination model is constructed by using PID control algorithm. Since the selection of PID parameters will affect the output of the model, this paper introduces particle swarm optimization algorithm to optimize the PID controller parameters globally, so that the PID controller can achieve the ideal control index, and finally determine the optimal combination of Matcha. The experimental results show that the method proposed in this paper can effectively realize the intelligent blending of Matcha, and maximize the cost of tea factory, effectively improve the income of Matcha products, which is conducive to the further development of tea companies.

Enhanced quality monitoring during black tea processing by the fusion of NIRS and computer vision

Polyphenol and catechin are key components in black tea processing, contributing to both taste and color quality. However, the rapid detection methods that are applicable throughout the processing stages are lacking. Here, we explored the potential of miniature near-infrared spectroscopy and self-built computer vision. Fresh tea leaves, and the samples from withering, rolling, fermentation, and drying steps were collected for in-situ data acquisition in a tea factory. Data from two sensors were fused, competitive adaptive reweighted sampling and Pearson correlation analysis were employed to select effective variables from spectral and color variables, respectively. And the linear partial least squares (PLS) were used for modeling. The results showed that PLS models based on low-level data fusion could not effectively improve the prediction accuracies compared to single data. By contrast, middle-level data fusion achieved the best prediction accuracies for both polyphenol and catechin, with average root mean square error of prediction of 0.66 ± 0.12 and 1.06 ± 0.11 g/100 g, and residual prediction deviations of 5.41 ± 0.99 and 4.03 ± 0.38, respectively. Overall, this study demonstrated the enhanced predictive capability of fused spectral and imaging systems for polyphenols, overcoming the low predictive accuracy of single sensors.

Impact of Rainfall Variability on Rural Tea Roads in Kericho, Kenya

Climate variability is a global phenomenon that is posing a threat to the infrastructure and agricultural sector. Intense precipitation often results in the deterioration of rural road infrastructure resulting in inaccessibility. Rainfall and temperature data from 1989 to 2019 was obtained from Kenya Meteorological Department. Data on Greenleaf and cost of repairs and maintenances are from selected tea factories managed by Kenya Tea Development Agency. Data on perception is based on a questionnaire survey of 398 randomly selected tea farmers. Results show that climate variability is experienced in Kericho (p < 0.005). There is a varsity variation in mean maximum temperatures F(0.05, 29) ꞊ 5.564 (p ꞊ 0.009) and mean minimum temperature F(29) =8.503 (p ꞊ 0.000). However, the linear regression analysis shows that rainfall has decreased (y ꞊ 2.5476x - 40.778) while the temperature has increased (y ꞊ 0.028x - 0.4473). There is a significant positive correlation between the amount of rainfall and cost of repairs and maintenances for five factories (r ꞊ 0.122, r = 0.046, r = 0.029, r = 0.255) except one (r = -.261, p ꞊ .466). Therefore, the climate has significantly varied from 1989-2019 and heavy rains occur periodically that damage rural tea roads, thus impacting negatively on tea transportation. There is a need, therefore, for heavy investment of emergency funds for repair and maintenance of rural tea roads based on rainfall variability and heavy rain return period pattern.

Two-stage distributionally robust mixed-integer optimization model for three-level location–allocation problems under uncertain environment

The problem of the optimal three-level location–allocation of the transfer center, processing factory, and distribution center for supply chain networks under uncertain transportation cost and customer demand is studied. We establish a two-stage distributionally robust 0–1 mixed-integer optimization model by considering the uncertainty of the supply chain. Given the complexity of the model, this paper proposes a distribution–separation hybrid intelligent algorithm (DS-HIA) to solve the resulting model, yielding the optimal location and maximal expected return of supply chain in the worst-case distribution. A case study of the tea supply chain in Shanghai is then presented to investigate the specific influence of uncertainties on a three-level location, i.e., transfer center, tea factory, and distribution center. Moreover, we compare the DS-HIA with distribution–separation hybrid second-order particle swarm optimization algorithm, distribution–separation hybrid particle swarm optimization, distribution–separation hybrid genetic algorithm and distributionally robust L-shaped method to validate the proposed algorithm based on the computational time and the convergence rate.

Application of sage herbal dust essential oils and supercritical fluid extract for the growth control of Escherichia coli in minced pork during storage

Sage has various biological activity and long tradition of the using in phytopharmaceutical preparations and, recently, in food industry. In this work, the essential oil obtained by hydrodistillation and essential oil and extract obtained by supercritical fluid extraction from sage herbal dust, waste product of filter tea factory, were screened for antimicrobial activity against Escherichia coli in the medium which simulates the conditions in meat and in real system of minced pork. The supercritical fluid extract had much lower effect to the reduction of a number of E. coli in meat simulation medium. The total inhibition of E. coli growth was achieved after 12 h and 24 h with the addition of 0.6 μl/ml of essential oil obtained by hydrodistilation and supercritical fluid extraction, respectively. The addition of essential oils and supercritical fluid extract of sage herbal dust could be used for the effective control of E. coli growth in minced meat.

Utilization of a Gas-Sensing System to Discriminate Smell and to Monitor Fermentation during the Manufacture of Oolong Tea Leaves.

The operational duration of shaking tea leaves is a critical factor in the manufacture of oolong tea; this duration influences the formation of its flavor and fragrance. The current method to control the duration of fermentation relies on the olfactory sense of tea masters; they monitor the entire process through their olfactory sense, and their experience decides the duration of shaking and setting. Because of this human factor and olfactory fatigue, it is difficult to define an optimum duration of shaking and setting; an inappropriate duration of shaking and setting deteriorates the quality of the tea. In this study, we used metal-oxide-semiconductor gas sensors to establish an electronic nose (E-nose) system and tested its feasibility. This research was divided into two experiments: distinguishing samples at various stages and an on-line experiment. The samples of tea leaves at various stages exhibited large differences in the level of grassy smell. From the experience of practitioners and from previous research, the samples could be categorized into three groups: before the first shaking (BS1), before the shaking group, and after the shaking group. We input the experimental results into a linear discriminant analysis to decrease the dimensions and to classify the samples into various groups. The results show that the smell can also be categorized into three groups. After distinguishing the samples with large differences, we conducted an on-line experiment in a tea factory and tried to monitor the smell variation during the manufacturing process. The results from the E-nose were similar to those of the sense of practitioners, which means that an E-nose has the possibility to replace the sensory function of practitioners in the future.

To My Grandmother. The Old Tea Factory at Kearsney, Natal

To My Grandmother. The Old Tea Factory at Kearsney, Natal

Comparative characteristics of white and black ceylon tea based on morphological features of the leaf

The central question of the research was addressed to comparative characteristics of white and black Ceylon tea based on morphological features of the leaf. The relevance of the study is due significant increasing falsifications of black and white tea on markets in Russia and all around the world. It should be noted that tea is still incomplete and insufficiently studied crop, despite its centuries-old use in human nutrition. Thus, the purpose of this work was to study the microstructure of black and white tea to identify differences in morphological characteristics of the leaf and develop markers for identifying its variety. The objects of study of this work were white and black varieties OP1 teas of Nandana Tea Factory (Sri Lanka). In our research were used research methods includes organoleptic and microscopical methods. According to the results micro- and macroscopic studies of black and white tea samples showed that there are significant morphological differences in the structure of leaves of different varieties, such as the size and density of hairs, the density of stomata, the location of druses and sclereids, and outgrowths of the leaf edge. These signs can serve as reliable markers for identifying the grade of tea.

FACTORS INFLUENCING SMALL FARMERS’ PARTICIPATION IN THE EXTENSION OF TEA FARMING: A CASE OF ILAM, NEPAL

Tea is one of Ilam’s most significant sources of foreign exchange as well as a source of employment and income for the farmers. The quality of Ilam tea is actually among the best in the world but the quantity is still a challenge. In order to increase the quantity of the orthodox tea, farmers are encouraged to extend tea farms. The extension of land under tea cultivation in previous years, Importance of being a member of a cooperative, the source of credit, off-farm employment, the harvest quantity influenced extension positively to farmers while education level, the main occupation did not influence the participation of the farmers in the extension of tea farming. Based on the results the study recommends increasing the farmer’s awareness to join the cooperative. It is suggested that the tea factory and infrastructures should be made easily available to minimize costs and increase benefits. The factors influencing small farmers' participation within the extension of tea farming were studied using both primary and secondary source of data through interviews with 196 tea farmers in Jitpur and Mangalbare areas of Ilam district as a case study. The participants were involved in tea cultivation at least for the last five years. In this study, a detailed analysis of the factors have been carried out. KEYWORDS- cooperative, extension, factors, orthodox tea, small farmers

Physico-chemical properties and associated active microbes of tea garden waste of Golaghat district of Assam, India

Tea Gardens generally produce two kinds of waste materials such as Tea Factory waste (TFW) and Pruning Litter (PL). Minimum 2 % of TFW is produced as by - product during processing of tea contributing a huge quantity as waste material.Similarly during pruning operations considerable amount of biomass are produced. Both the bio-waste materials can be managed by biological process to produce value added organic supplement to enrich the soil of tea plantation. During the present study different physico-chemical properties, viz. pH, P2O2 , K2O and nitrogen’s of TFW were analyzed. In TFW the value of Total soluble solids ranged (27.2-31.1%) and Crude fiber ranged (25.83-31.12%) and Caffenine amount ranged (23.14- 27.94%) and Total ash ranged (3.15-6.54%) The aflavin ranged (0.45-0.76%) and the arubignins ranged (18.45-21.32%). In TFW and PL some beneficial and active microbial populations are found which can be used in tea plants after making value added compost to increase their natural productivity. In this study focus was given to explore the beneficial and active microorganisms found in TFW and PL and found some beneficial microbes such as Actinomycetes, Azotobacter, Azospirillum and Phosphate solubilizing bacteria respectively

Potential management interventions to mitigate greenhouse gas emissions from tea cultivation

Previous studies have confirmed the agricultural stage as an important contributor to total tea life cycle greenhouse gas (GHG) emissions. We therefore focus on the growing and processing of black tea and evaluate the GHG reduction potential of possible agricultural management interventions for tea produced from Unilever’s tea estates and factories in Kenya. A baseline GHG footprint was calculated using data collected over four years. Potential interventions to reduce the GHG footprint per kg of black tea focused on key drivers (yield and fertiliser use) of the GHG footprint. These interventions and their effects on production are evidence-based but hypothetical and relate to possible changes in: (1) Harvesting practices; (2) Fertiliser application (timing) and (3) Organic production. Improvements in fertiliser application and harvesting practices could potentially deliver 16% and 9% reduction in GHG emissions, respectively. Under favourable conditions (sourcing fertiliser locally and no yield decline), changing to organic production could theoretically deliver 25% reduction in GHG emissions. However, under less favourable conditions (European sourced fertiliser and 30% yield decline), GHG emissions could increase by 41%. The availability of locally sourced organic fertiliser, sufficient to maintain nitrogen application rates, is seen as the biggest challenge in delivering sustainable organic tea cultivation.

Characterization of Switching Transients in Low Voltage Power Systems of Tea Factories in Sri Lanka

Voltage transients caused by various motors and electrical equipment of tea factories in Sri Lanka have been observed and analyzed. While reporting the major components of transients, this work extends it aspires to investigate the risk of having faults in a three-phase induction motor by monitoring and analyzing the transient voltage waveforms during the starting period. Therefore, common mode transient investigations have been followed. Transient voltage signals have been obtained from high end test setup and altogether 588 waveforms have been analyzed in both the time and frequency domains. In DOL and Star-Delta starting, highest transient amplitude of 688.2 V and 572.1 V have been observed respectively. Highest transient amplitude of 976.4 V and 980.5 V were observed in DOL and Star-Delta switching respectively. Withering and rolling sections dominates over other stages, generating high amplitude transients in average, reflecting same endangerment in energy calculations as presented in voltage integral. DOL starting transients carries fast rise times as 14 ns and in Star-Delta it is 28 ns. In order to assist with the exegesis of these data, transient parameters like rise time, duration, highest peak, etc.… have also been presented in statistical basis.

The efficiency of kaizen costing system in reducing non-value activities

Modern trends, economic development and technological progress further intensify competition. Thus, in the context of growing competition, the attention of enterprises is focused on non-value activities, i.e. on activities that have no value and associated costs. This is due to the fact that activities of no value in enterprises lead to increased costs and reduced profits. Non-value actions can be observed during the entire course of the company activities. To do this, it is necessary to pay special attention to the fact that values are not formed as a result of actions of the enterprise. Non-value actions in the enterprise include unnecessary materials, packaging, poor quality, production losses, excess inventory, unnecessary transportation, additional control, unproductive working hours, etc. Thus, in this study, the impact of the Kaizen cost calculation system on eliminating or reducing useless activities in the production process was studied using a semi-structured interview at a dry tea factory. The study focuses only on losses in the production process and does not take into account actions that do not create value other than production losses, i.e. are useless. Based on the results of the study, we can say that the Kaizen cost calculation system has a positive effect on reducing production losses (defective production, idle production, excess and waste), which are one of the actions that have no value.

Artefak Kolonial Perkebunan Panglejar, Maswati, Rajamandala Masa Hindia Belanda: Arti dan Arah Sejarah

Colonial plantation artifacts are an important cultural in the history of plantation at Bandung, West Java. What and how the plantation artifacts are the main problem in this paper. the purpose of this paper is to explain the colonial plantation artifacts in the form of inscriptions and old maps of the garden. The method used is a desk research on archeological research reports, books, and the internet. The data sources obtained are the inscription of the establishment of the old Panglejar tea factory in the IHT Building, the inscription of the establishment of the Administrator of Maswati Plantation house in the Pusdiklat Building, and the old map of the Rajamandala P lantation in the Office of Rajamandala Afdeling 1 of Panglejar Platation. The three colonial artifacts give special meaning to the continuity of plantation history since the days of the Dutch East Indies until now, as well as showing directions to search for and find historical information through colonial archival research and information from interviews with relevant informants at the present time.

VALUE CHAIN ANALYSIS OF ORTHODOX TEA IN ILAM DISTRICT OF NEPAL

Despite of the high rate of the orthodox tea, the net margin is still below the satisfactory level. Thus the present research was conducted to analyze the value chain of orthodox tea in Ilam district of Nepal. A total of 160 samples were collected, 80 each from organic and conventional tea growing area. Similarly, 4 tea processing factories and 5 local traders were selected purposely. The major functions involved in the orthodox tea value chain were supplying of the inputs, production, transportation/collection, processing, blending and packaging, exporting and domestic trading. Agro vets and input suppliers supplied required inputs such as saplings, fertilizers and pesticides etc. to the farmers and tea estates. The production of green tea leaves would undergo transportation and collection which was conducted by farmers, tea estates, co-operatives and brokers. Processing, blending and packaging functions were carried out either by tea companies or tea processing factories. Exportation was conducted by tea factories or trading companies whereas domestic trading was conducted by tea factories, wholesaler and retailers. Low farm gate price, high cost of labor and inputs were the major production problems whereas fluctuation in price and lack of marketing information were the major marketing problems from the study.

EVALUATION OF WASTE MANAGEMENT SYSTEMS IN A KENYAN TEA FACTORY: A CASE STUDY OF MARAMBA TEA FACTORY IN KIAMBU COUNTY

This paper evaluates the effectiveness of waste management systems in Maramba Tea Factory in Kiambu County, Kenya. Performance of the already existing systems is therefore critical in sustaining our environment. Tea processing generates different types of wastes. A waste management system design should at least begin from a clear characterization of these wastes, the quantities and qualities of the wastes and identification of sources. This study attempted to bring these challenges to the fore. It evaluated the waste management systems for Maramba Tea factory in Kiambu County, Kenya. Primary data and secondary data, Purposively and Convenience sampling techniques, Benchmarking evaluation technique were utilised. The types of wastes identified were organic solid wastes, inorganic solid wastes, Liquid wastes and Thermal wastes. The quantities of wastes were determined by weighing. The Organic solid wastes from tea processing stages was 486.47 kilograms per month and inorganic solid wastes (sacks and polythene bags) was 15.38 kilograms per month. The amount of liquid wastes generated for the study period were estimated. The highest with major cleaning done weekly averaged of 139.4m3 and least with minor cleaning done daily averaged at 52.8m3. The thermal wastes generated was due to heat loss from the wood fuel used as a source of energy. The total amount of heat loss was 1145.51kcal/kg representing 37.45%. of the Gross Calorific Value (GCV) of wood fuel. The highest heat loss was due to dry flue gas with a 22.09% of GCV of wood fuel representing 675.85kcal/kg and the least due to moisture present in the combustion air at 24.78kcal/kg representing 0.810 % of the total GCV of wood fuel. The qualities of wastewater were achieved through analysing the BOD5, COD, pH and Electrical conductivity and comparing the values to the standards recommended by National Environment Management Authority (NEMA). The BOD5 at 83.7mg/L and COD at 106.63mg/L exceeded the NEMA limits of 30mg/L and 50mg/L respectively. The thermal waste systems were evaluated by determining the boiler efficiency. Boiler efficiency at Maramba Tea Factory was 62.55%. The boiler efficiency of 62.55% is lower compared to the set values of 75.01% and 75%. The analysis with ANOVA showed significant differences in the water parameter values from source through the lagoon to the river. The coefficient of determination (R2) for most of the parameter analysed were above 97%. It was concluded that the waste management systems are only partially effective at Maramba Tea Factory. More targeted studies need to be carried out in other food industries to make a general conclusion on the state of waste management systems in Kenya.

Top Management Team Characteristics, Competitive Environment and Strategy Implementation

Competing favorably in the market requires finding a perfect fit between a firm’s resources and the business environment. Strategy is the stewardship by top management that aligns organizational resources and capabilities to the environment with the ultimate goal of achieving superior and sustainable performance. The current study was designed to determine the influence of competitive environment on the relationship between top management team characteristics and strategy implementation. The study adopted the descriptive cross-sectional survey design. Data was obtained by administering structured questionnaire mailed to top managers in tea factory companies in Kenya. The moderation test was carried out using the product term of the standardized scores for top management team characteristics and competitive environment respectively. Data was processed through regression analysis. While we demonstrate that top management team characteristics had significant influence on strategy implementation, the results of moderation tests were not statistically significant. Consequently, our hypothesized moderating influence of competitive environment on the relationship between top management team characteristics and strategy implementation was not supported. Our findings raise theoretical questions on whether competitive environment is more relevant during strategy formulation process or execution stage. We conclude that companies implementing strategy in stable competitive environment have predictable implementation of planned strategy. We further conclude that external insulation from competition by umbrella marketing agency reduces the influence of factors within the competitive environment on the relationship between top management team characteristics and strategy implementation. However, the temporary insulation of the firm from competition exposes it to competitive disadvantage in the event that the marketing agency is destabilized by forces both from within and external to it.

A novel use of solid waste extract from tea factory as corrosion inhibitor in acidic media on boiler quality steel

Solid waste from a tea factory was used to prepare environment-friendly, inexpensive “green corrosion inhibitor”. The solid tea waste extract (STWE) was prepared from the solid waste by the conventional extraction method and characterized by liquid chromatography–mass spectroscopy (LC–MS). The inhibition performance of this synthesized STWE was evaluated in 1 (M) HCl on boiler quality (BQ) steel. Their efficiency of inhibition was assessed by electrochemical techniques, namely the potentiodynamic polarization test (PDP), electrochemical impedance spectroscopy (EIS). The results depict that the increase in the concentration of STWE increases the inhibition efficiency of the extract. Various models were fitted to explore the type of adsorption, and among them, Langmuir was found fitted best. The free energy ΔGads° was calculated as -17.76 KJmol−1 from adsorption isotherm and, revealed physisorption of STWE on the BQ surface. The inhibitive strength or effectiveness of inhibitor molecules was assessed based on donor-acceptor capabilities between the molecules and the metallic surface. This capability was evaluated with the help of quantum chemical calculations based on density functional theory.

An Optimum Tea Fermentation Detection Model Based on Deep Convolutional Neural Networks

Tea is one of the most popular beverages in the world, and its processing involves a number of steps which includes fermentation. Tea fermentation is the most important step in determining the quality of tea. Currently, optimum fermentation of tea is detected by tasters using any of the following methods: monitoring change in color of tea as fermentation progresses and tasting and smelling the tea as fermentation progresses. These manual methods are not accurate. Consequently, they lead to a compromise in the quality of tea. This study proposes a deep learning model dubbed TeaNet based on Convolution Neural Networks (CNN). The input data to TeaNet are images from the tea Fermentation and Labelme datasets. We compared the performance of TeaNet with other standard machine learning techniques: Random Forest (RF), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Naive Bayes (NB). TeaNet was more superior in the classification tasks compared to the other machine learning techniques. However, we will confirm the stability of TeaNet in the classification tasks in our future studies when we deploy it in a tea factory in Kenya. The research also released a tea fermentation dataset that is available for use by the community.